12,291 research outputs found

    Ontology-Based MEDLINE Document Classification

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    An increasing and overwhelming amount of biomedical information is available in the research literature mainly in the form of free-text. Biologists need tools that automate their information search and deal with the high volume and ambiguity of free-text. Ontologies can help automatic information processing by providing standard concepts and information about the relationships between concepts. The Medical Subject Headings (MeSH) ontology is already available and used by MEDLINE indexers to annotate the conceptual content of biomedical articles. This paper presents a domain-independent method that uses the MeSH ontology inter-concept relationships to extend the existing MeSH-based representation of MEDLINE documents. The extension method is evaluated within a document triage task organized by the Genomics track of the 2005 Text REtrieval Conference (TREC). Our method for extending the representation of documents leads to an improvement of 17% over a non-extended baseline in terms of normalized utility, the metric defined for the task. The SVMlight software is used to classify documents

    Visualizing the semantic content of large text databases using text maps

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    A methodology for generating text map representations of the semantic content of text databases is presented. Text maps provide a graphical metaphor for conceptualizing and visualizing the contents and data interrelationships of large text databases. Described are a set of experiments conducted against the TIPSTER corpora of Wall Street Journal articles. These experiments provide an introduction to current work in the representation and visualization of documents by way of their semantic content

    Cross-lingual document retrieval categorisation and navigation based on distributed services

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    The widespread use of the Internet across countries has increased the need for access to document collections that are often written in languages different from a user’s native language. In this paper we describe Clarity, a Cross Language Information Retrieval (CLIR) system for English, Finnish, Swedish, Latvian and Lithuanian. Clarity is a fully-fledged retrieval system that supports the user during the whole process of query formulation, text retrieval and document browsing. We address four of the major aspects of Clarity: (i) the user-driven methodology that formed the basis for the iterative design cycle and framework in the project, (ii) the system architecture that was developed to support the interaction and coordination of Clarity’s distributed services, (iii) the data resources and methods for query translation, and (iv) the support for Baltic languages. Clarity is an example of a distributed CLIR system built with minimal translation resources and, to our knowledge, the only such system that currently supports Baltic languages

    Designing a Semantically Rich Visual Iinterface for Cultural Digital Libraries Using the UNESCO Multilingual Thesaurus

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    This paper reports on the design of a visual user interface for the UNESCO digital portal. The interface makes use of the UNESCO multilingual thesaurus to provide visualized views of terms and their relationships and the way in which spaces associated with the thesaurus, the query and the results can be integrated into a single user interface.\u

    Designing a semantically rich visual interface for cultural digital libraries using the UNEsCO multilingual thesaurus

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    This paper reports on the design of a visual user interface for the UNESCO digital portal. The interface makes use of the UNESCO multilingual thesaurus to provide visualized views of terms and their relationships and the way in which spaces associated with the thesaurus, the query and the results can be integrated into a single user interface
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